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Using Bootstrapped Confidence Intervals for Improved Inferences with Seemingly Unrelated Regression Equations

Published online by Cambridge University Press:  11 February 2009

Paul Rilstone  and
Michael Veall
Paul Rilstone
Affiliation:
York University
Michael Veall
Affiliation:
McMaster University
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Abstract

The usual standard errors for the regression coefficients in a seemingly unrelated regression model have a substantial downward bias. Bootstrapping the standard errors does not seem to improve inferences. In this paper, Monte Carlo evidence is reported which indicates that bootstrapping can result in substantially better inferences when applied to t-ratios rather than to standard errors.

Type
Research Article
Information
Econometric Theory , Volume 12 , Issue 3 , August 1996 , pp. 569 - 580
Copyright
Copyright © Cambridge University Press 1996

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References

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